Run this test program and see if it does what you want. It uses sashelp.class -- so you should be able to run it. You really only care about the array technique used in the second Data step program, but I needed to make up some missing data to test the program.
** make some data with missing values;
if age = 13 then height = .;
else if age = 12 then weight = .;
else if age = 15 then do;
height = .;
weight = .;
proc print data=newclass;
title 'should have some missing';
** For every observations, treat the numeric vars as though;
** they are in an array and use a do loop to set missing;
** to 0;
array fix(*) _numeric_;
do i = 1 to dim(fix);
fix(i) = sum(fix(i),0);
proc print data=fixmiss;
title 'missing should be fixed';
SAS data step code makes it easy to reference name prefix lists (e.g. all variables starting with q_) but unfortunately not what you're describing with a common suffix. In order to do that, I would write some SAS code to create a list of variable names as the value for a macro variable, then reference that macro variable in data step code similar to what Cynthia showed above.
Run the following code, then use the final data step shown by Cynthia. However, in that code, replace _numeric_ on the ARRAY statement with &qlist (the name of the macro variable we created). That should do the trick.
/* Create test data set */
if mod(_N_,2) = 1 then height=.;
/* Every second height missing */
if mod(_N_,5) = 1 then age=.;
/* Every fifth age missing */
rename height=height_q age=age_q;
proc sql noprint;
into : qlist separated by ", "
and upcase(name) like '%_Q';